Wald tests for IV regression with weak instruments

Detalhes bibliográficos
Autor(a) principal: Vilela, Lucas Pimentel
Data de Publicação: 2013
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: https://hdl.handle.net/10438/11222
Resumo: This dissertation deals with the problem of making inference when there is weak identification in models of instrumental variables regression. More specifically we are interested in one-sided hypothesis testing for the coefficient of the endogenous variable when the instruments are weak. The focus is on the conditional tests based on likelihood ratio, score and Wald statistics. Theoretical and numerical work shows that the conditional t-test based on the two-stage least square (2SLS) estimator performs well even when instruments are weakly correlated with the endogenous variable. The conditional approach correct uniformly its size and when the population F-statistic is as small as two, its power is near the power envelopes for similar and non-similar tests. This finding is surprising considering the bad performance of the two-sided conditional t-tests found in Andrews, Moreira and Stock (2007). Given this counter intuitive result, we propose novel two-sided t-tests which are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test of Moreira (2003).
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spelling Vilela, Lucas PimentelEscolas::EPGEFGVMedeiros, Marcelo CunhaAlmeida, Caio Ibsen Rodrigues deMoreira, Marcelo Jovita2013-10-14T14:45:02Z2013-10-14T14:45:02Z2013-09-17VILELA, Lucas Pimentel. Wald tests for IV regression with weak instruments. Dissertação (Mestrado em Economia) - FGV - Fundação Getúlio Vargas, Rio de Janeiro, 2013.https://hdl.handle.net/10438/11222This dissertation deals with the problem of making inference when there is weak identification in models of instrumental variables regression. More specifically we are interested in one-sided hypothesis testing for the coefficient of the endogenous variable when the instruments are weak. The focus is on the conditional tests based on likelihood ratio, score and Wald statistics. Theoretical and numerical work shows that the conditional t-test based on the two-stage least square (2SLS) estimator performs well even when instruments are weakly correlated with the endogenous variable. The conditional approach correct uniformly its size and when the population F-statistic is as small as two, its power is near the power envelopes for similar and non-similar tests. This finding is surprising considering the bad performance of the two-sided conditional t-tests found in Andrews, Moreira and Stock (2007). Given this counter intuitive result, we propose novel two-sided t-tests which are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test of Moreira (2003).Esta dissertação trata do problema de inferência na presença de identificação fraca em modelos de regresso com variáveis instrumentais. Mais especificamente em testes de hipóteses com relação ao parâmetro da variável endógena quando os instrumentos são fracos. O principal foco é nos testes condicionais unilaterais baseados nas estatísticas de razão de máxima verossimilhança, score e Wald. Resultados teóricos e numéricos mostram que o teste t condicional unilateral baseado no estimador de mínimos quadrados em dois estágios tem uma boa performance mesmo na presença de instrumentos fracamente correlacionados com a variável endógena. A abordagem condicional corrige uniformemente o tamanho do teste t e quando a estatística F populacional é tão pequena quanto dois, o poder do teste é próximo ao power envelope tanto de testes similares quanto de não similares. Tal resultado é surpreendente visto a má performance dos testes t’s condicionais bilaterais relatada em (6, Andrews, Moreira and Stock (2007)). Dado esse resultado aparentemente contra intuitivo, apresentamos novos testes t’s condicionals bilaterais que são aproximadamente não viesados e performam, em alguns casos, tão bem quanto o teste condicional baseado na estatística de razão de verossimilhança de ( 19 , Moreira (2003)).engInstrumental variable regressionInvariant testsOptimal testsSimilar testsUnbiased testsWeak instrumentsRegressão com variáveis instrumentaisTestes invariantesTestes ótimosTestes similaresTestes não viesadosInstrumentos fracosEconomiaVariáveis instrumentais (Estatística)Análise de regressãoTestes de hipóteses estatísticasWald tests for IV regression with weak instrumentsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas 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dc.title.eng.fl_str_mv Wald tests for IV regression with weak instruments
title Wald tests for IV regression with weak instruments
spellingShingle Wald tests for IV regression with weak instruments
Vilela, Lucas Pimentel
Instrumental variable regression
Invariant tests
Optimal tests
Similar tests
Unbiased tests
Weak instruments
Regressão com variáveis instrumentais
Testes invariantes
Testes ótimos
Testes similares
Testes não viesados
Instrumentos fracos
Economia
Variáveis instrumentais (Estatística)
Análise de regressão
Testes de hipóteses estatísticas
title_short Wald tests for IV regression with weak instruments
title_full Wald tests for IV regression with weak instruments
title_fullStr Wald tests for IV regression with weak instruments
title_full_unstemmed Wald tests for IV regression with weak instruments
title_sort Wald tests for IV regression with weak instruments
author Vilela, Lucas Pimentel
author_facet Vilela, Lucas Pimentel
author_role author
dc.contributor.unidadefgv.por.fl_str_mv Escolas::EPGE
dc.contributor.affiliation.none.fl_str_mv FGV
dc.contributor.member.none.fl_str_mv Medeiros, Marcelo Cunha
Almeida, Caio Ibsen Rodrigues de
dc.contributor.author.fl_str_mv Vilela, Lucas Pimentel
dc.contributor.advisor1.fl_str_mv Moreira, Marcelo Jovita
contributor_str_mv Moreira, Marcelo Jovita
dc.subject.eng.fl_str_mv Instrumental variable regression
Invariant tests
Optimal tests
Similar tests
Unbiased tests
Weak instruments
topic Instrumental variable regression
Invariant tests
Optimal tests
Similar tests
Unbiased tests
Weak instruments
Regressão com variáveis instrumentais
Testes invariantes
Testes ótimos
Testes similares
Testes não viesados
Instrumentos fracos
Economia
Variáveis instrumentais (Estatística)
Análise de regressão
Testes de hipóteses estatísticas
dc.subject.por.fl_str_mv Regressão com variáveis instrumentais
Testes invariantes
Testes ótimos
Testes similares
Testes não viesados
Instrumentos fracos
dc.subject.area.por.fl_str_mv Economia
dc.subject.bibliodata.por.fl_str_mv Variáveis instrumentais (Estatística)
Análise de regressão
Testes de hipóteses estatísticas
description This dissertation deals with the problem of making inference when there is weak identification in models of instrumental variables regression. More specifically we are interested in one-sided hypothesis testing for the coefficient of the endogenous variable when the instruments are weak. The focus is on the conditional tests based on likelihood ratio, score and Wald statistics. Theoretical and numerical work shows that the conditional t-test based on the two-stage least square (2SLS) estimator performs well even when instruments are weakly correlated with the endogenous variable. The conditional approach correct uniformly its size and when the population F-statistic is as small as two, its power is near the power envelopes for similar and non-similar tests. This finding is surprising considering the bad performance of the two-sided conditional t-tests found in Andrews, Moreira and Stock (2007). Given this counter intuitive result, we propose novel two-sided t-tests which are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test of Moreira (2003).
publishDate 2013
dc.date.accessioned.fl_str_mv 2013-10-14T14:45:02Z
dc.date.available.fl_str_mv 2013-10-14T14:45:02Z
dc.date.issued.fl_str_mv 2013-09-17
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv VILELA, Lucas Pimentel. Wald tests for IV regression with weak instruments. Dissertação (Mestrado em Economia) - FGV - Fundação Getúlio Vargas, Rio de Janeiro, 2013.
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10438/11222
identifier_str_mv VILELA, Lucas Pimentel. Wald tests for IV regression with weak instruments. Dissertação (Mestrado em Economia) - FGV - Fundação Getúlio Vargas, Rio de Janeiro, 2013.
url https://hdl.handle.net/10438/11222
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional do FGV (FGV Repositório Digital)
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institution FGV
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repository.name.fl_str_mv Repositório Institucional do FGV (FGV Repositório Digital) - Fundação Getulio Vargas (FGV)
repository.mail.fl_str_mv
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